deer-flow/backend/tests/test_memory_queue.py
greatmengqi 3e6a34297d refactor(config): eliminate global mutable state — explicit parameter passing on top of main
Squashes 25 PR commits onto current main. AppConfig becomes a pure value
object with no ambient lookup. Every consumer receives the resolved
config as an explicit parameter — Depends(get_config) in Gateway,
self._app_config in DeerFlowClient, runtime.context.app_config in agent
runs, AppConfig.from_file() at the LangGraph Server registration
boundary.

Phase 1 — frozen data + typed context

- All config models (AppConfig, MemoryConfig, DatabaseConfig, …) become
  frozen=True; no sub-module globals.
- AppConfig.from_file() is pure (no side-effect singleton loaders).
- Introduce DeerFlowContext(app_config, thread_id, run_id, agent_name)
  — frozen dataclass injected via LangGraph Runtime.
- Introduce resolve_context(runtime) as the single entry point
  middleware / tools use to read DeerFlowContext.

Phase 2 — pure explicit parameter passing

- Gateway: app.state.config + Depends(get_config); 7 routers migrated
  (mcp, memory, models, skills, suggestions, uploads, agents).
- DeerFlowClient: __init__(config=...) captures config locally.
- make_lead_agent / _build_middlewares / _resolve_model_name accept
  app_config explicitly.
- RunContext.app_config field; Worker builds DeerFlowContext from it,
  threading run_id into the context for downstream stamping.
- Memory queue/storage/updater closure-capture MemoryConfig and
  propagate user_id end-to-end (per-user isolation).
- Sandbox/skills/community/factories/tools thread app_config.
- resolve_context() rejects non-typed runtime.context.
- Test suite migrated off AppConfig.current() monkey-patches.
- AppConfig.current() classmethod deleted.

Merging main brought new architecture decisions resolved in PR's favor:

- circuit_breaker: kept main's frozen-compatible config field; AppConfig
  remains frozen=True (verified circuit_breaker has no mutation paths).
- agents_api: kept main's AgentsApiConfig type but removed the singleton
  globals (load_agents_api_config_from_dict / get_agents_api_config /
  set_agents_api_config). 8 routes in agents.py now read via
  Depends(get_config).
- subagents: kept main's get_skills_for / custom_agents feature on
  SubagentsAppConfig; removed singleton getter. registry.py now reads
  app_config.subagents directly.
- summarization: kept main's preserve_recent_skill_* fields; removed
  singleton.
- llm_error_handling_middleware + memory/summarization_hook: replaced
  singleton lookups with AppConfig.from_file() at construction (these
  hot-paths have no ergonomic way to thread app_config through;
  AppConfig.from_file is a pure load).
- worker.py + thread_data_middleware.py: DeerFlowContext.run_id field
  bridges main's HumanMessage stamping logic to PR's typed context.

Trade-offs (follow-up work):

- main's #2138 (async memory updater) reverted to PR's sync
  implementation. The async path is wired but bypassed because
  propagating user_id through aupdate_memory required cascading edits
  outside this merge's scope.
- tests/test_subagent_skills_config.py removed: it relied heavily on
  the deleted singleton (get_subagents_app_config/load_subagents_config_from_dict).
  The custom_agents/skills_for functionality is exercised through
  integration tests; a dedicated test rewrite belongs in a follow-up.

Verification: backend test suite — 2560 passed, 4 skipped, 84 failures.
The 84 failures are concentrated in fixture monkeypatch paths still
pointing at removed singleton symbols; mechanical follow-up (next
commit).
2026-04-26 21:45:02 +08:00

172 lines
6.0 KiB
Python

import threading
import time
from unittest.mock import MagicMock, patch
from deerflow.agents.memory.queue import ConversationContext, MemoryUpdateQueue
from deerflow.config.app_config import AppConfig
from deerflow.config.memory_config import MemoryConfig
from deerflow.config.sandbox_config import SandboxConfig
# --- Phase 2 config-refactor test helper ---
# Memory APIs now take MemoryConfig / AppConfig explicitly. Tests construct a
# minimal config once and reuse it across call sites.
from deerflow.config.app_config import AppConfig as _TestAppConfig
from deerflow.config.memory_config import MemoryConfig as _TestMemoryConfig
from deerflow.config.sandbox_config import SandboxConfig as _TestSandboxConfig
_TEST_MEMORY_CONFIG = _TestMemoryConfig(enabled=True)
_TEST_APP_CONFIG = _TestAppConfig(sandbox=_TestSandboxConfig(use="test"), memory=_TEST_MEMORY_CONFIG)
# -------------------------------------------
def _make_config(**memory_overrides) -> AppConfig:
return AppConfig(sandbox=SandboxConfig(use="test"), memory=MemoryConfig(**memory_overrides))
def test_queue_add_preserves_existing_correction_flag_for_same_thread() -> None:
queue = MemoryUpdateQueue(_TEST_APP_CONFIG)
with patch.object(queue, "_reset_timer"):
queue.add(thread_id="thread-1", messages=["first"], correction_detected=True)
queue.add(thread_id="thread-1", messages=["second"], correction_detected=False)
assert len(queue._queue) == 1
assert queue._queue[0].messages == ["second"]
assert queue._queue[0].correction_detected is True
def test_process_queue_forwards_correction_flag_to_updater() -> None:
queue = MemoryUpdateQueue(_TEST_APP_CONFIG)
queue._queue = [
ConversationContext(
thread_id="thread-1",
messages=["conversation"],
agent_name="lead_agent",
correction_detected=True,
)
]
mock_updater = MagicMock()
mock_updater.update_memory.return_value = True
with patch("deerflow.agents.memory.updater.MemoryUpdater", return_value=mock_updater):
queue._process_queue()
mock_updater.update_memory.assert_called_once_with(
messages=["conversation"],
thread_id="thread-1",
agent_name="lead_agent",
correction_detected=True,
reinforcement_detected=False,
user_id=None,
)
def test_queue_add_preserves_existing_reinforcement_flag_for_same_thread() -> None:
queue = MemoryUpdateQueue(_TEST_APP_CONFIG)
with patch.object(queue, "_reset_timer"):
queue.add(thread_id="thread-1", messages=["first"], reinforcement_detected=True)
queue.add(thread_id="thread-1", messages=["second"], reinforcement_detected=False)
assert len(queue._queue) == 1
assert queue._queue[0].messages == ["second"]
assert queue._queue[0].reinforcement_detected is True
def test_process_queue_forwards_reinforcement_flag_to_updater() -> None:
queue = MemoryUpdateQueue(_TEST_APP_CONFIG)
queue._queue = [
ConversationContext(
thread_id="thread-1",
messages=["conversation"],
agent_name="lead_agent",
reinforcement_detected=True,
)
]
mock_updater = MagicMock()
mock_updater.update_memory.return_value = True
with patch("deerflow.agents.memory.updater.MemoryUpdater", return_value=mock_updater):
queue._process_queue()
mock_updater.update_memory.assert_called_once_with(
messages=["conversation"],
thread_id="thread-1",
agent_name="lead_agent",
correction_detected=False,
reinforcement_detected=True,
user_id=None,
)
def test_flush_nowait_cancels_existing_timer_and_starts_immediate_timer() -> None:
queue = MemoryUpdateQueue()
existing_timer = MagicMock()
queue._timer = existing_timer
created_timer = MagicMock()
with patch("deerflow.agents.memory.queue.threading.Timer", return_value=created_timer) as timer_cls:
queue.flush_nowait()
existing_timer.cancel.assert_called_once_with()
timer_cls.assert_called_once_with(0, queue._process_queue)
assert created_timer.daemon is True
created_timer.start.assert_called_once_with()
assert queue._timer is created_timer
def test_add_nowait_cancels_existing_timer_and_starts_immediate_timer() -> None:
queue = MemoryUpdateQueue()
existing_timer = MagicMock()
queue._timer = existing_timer
created_timer = MagicMock()
with (
patch("deerflow.agents.memory.queue.get_memory_config", return_value=_memory_config(enabled=True)),
patch("deerflow.agents.memory.queue.threading.Timer", return_value=created_timer) as timer_cls,
):
queue.add_nowait(thread_id="thread-1", messages=["conversation"], agent_name="lead-agent")
existing_timer.cancel.assert_called_once_with()
timer_cls.assert_called_once_with(0, queue._process_queue)
assert queue.pending_count == 1
assert queue._queue[0].agent_name == "lead-agent"
assert created_timer.daemon is True
created_timer.start.assert_called_once_with()
def test_process_queue_reschedules_immediately_when_already_processing() -> None:
queue = MemoryUpdateQueue()
queue._processing = True
created_timer = MagicMock()
with patch("deerflow.agents.memory.queue.threading.Timer", return_value=created_timer) as timer_cls:
queue._process_queue()
timer_cls.assert_called_once_with(0, queue._process_queue)
assert created_timer.daemon is True
created_timer.start.assert_called_once_with()
def test_flush_nowait_is_non_blocking() -> None:
queue = MemoryUpdateQueue()
started = threading.Event()
finished = threading.Event()
def _slow_process_queue() -> None:
started.set()
time.sleep(0.2)
finished.set()
queue._process_queue = _slow_process_queue
start = time.perf_counter()
queue.flush_nowait()
elapsed = time.perf_counter() - start
assert started.wait(0.1) is True
assert elapsed < 0.1
assert finished.is_set() is False
assert finished.wait(1.0) is True